Enhancing Passenger Flow at Subway Transfer Stations Through Simulation Modeling

With the increased popularity of the public transportation field, congestion in multi-line subway transfer hubs has become one of the hot issues. This study presents a comprehensive simulation model utilizing AnyLogic software to evaluate the performance of the 59th-Street-Columbus Circle subway transfer station in New York City by addressing challenges of inefficient passenger flow management. Leveraging the NYC turnstile usage data, the simulation focuses on this major three-level transfer hub to analyze passenger flows, identify bottlenecks, and evaluate potential solutions. Extensive simulation experiments reveal criti-cal high-density regions prone to severe congestion, particularly at intersections. With an inverse relation-ship between crowd density and average passenger speed, higher densities lead to near-stagnant conditions during peak hours. By providing data-driven insights through simulation analyses, this research aims to enhance the commuter experience, reduce delays, ensure efficient behavior at vital transit hubs, and contri-bute to more-sustainable urban transportation by encouraging public transit usage.